A thread through the archive
Essays tagged “Bayesian reasoning”. Follow an idea across the archive.
Scott explains why he's not interested in participating in the current wave of God debates on Substack, arguing that religious explanations fall into the same category as conspiracy theories by invoking "powerful hidden entities" to explain anomalies.
Scott explores reader responses to his Fatima miracle post, finding the most promising explanation in Buddhist fire kasina meditation practices that produce similar visual phenomena, while remaining uncertain about how 70,000 untrained people could achieve advanced meditative states instantly.
Brandon Hendrickson presents a method to teach Bayes' theorem effectively to everyone by making it visual, intuitive, emotionally engaging, and a tool for rational discourse.
Scott Alexander reviews a $100,000 debate on COVID-19 origins, where the zoonotic hypothesis unexpectedly won against the lab leak theory.
Scott Alexander argues against significantly updating beliefs based on single dramatic events, advocating for consistent policies based on pre-existing probability distributions.
Scott Alexander criticizes the misleading use of 'no evidence' in science communication and suggests more nuanced alternatives.
Scott Alexander proposes a Bayesian theory of willpower as a process of weighing evidence from different mental processes to determine actions.
Scott Alexander explores the concept of 'trapped priors' as a fundamental problem in rationality, explaining how it leads to persistent biases and suggesting potential solutions.
Scott Alexander proposes that confirmation bias might be a misapplication of normal Bayesian reasoning rather than a separate cognitive phenomenon.
Scott Alexander argues that non-empirical reasoning, based on principles like simplicity and elegance, is a necessary and legitimate part of scientific practice, even for evaluating seemingly untestable theories.
Scott Alexander examines skeptical and supportive comments on claims of enlightenment, arguing that evidence for such states is comparable to other accepted mental phenomena.
Scott reviews a paper proposing that psychedelics work by relaxing priors in the brain, potentially treating mental illness but also risking side effects.
Scott Alexander argues that Free Energy/Predictive Coding and Perceptual Control Theory are fundamentally the same, and proposes using PCT's more intuitive terminology to help understand FE/PC.
Scott Alexander presents a 'Grand Unified Chart' showing how different domains of knowledge share a similar structure in interpreting the world, arguing this is due to basic brain algorithms and effective epistemology.
Scott Alexander examines the conflict between predictive processing theory and evolutionary psychology claims about innate knowledge, questioning how genes could directly encode complex preferences.
Scott Alexander warns against forming strong heuristics based on limited data, using examples from AI research, elections, and campaign strategies to illustrate the pitfalls of this approach.
The post explores how Bayesian processes in the brain might explain perception and various mental disorders, linking neurotransmitters to different aspects of Bayesian reasoning.
Scott Alexander argues that psychology is indeed in crisis, contrary to a New York Times article's claim, due to issues like publication bias and low replication rates.
Scott Alexander defends Less Wrong and Eliezer Yudkowsky against accusations of being anti-scientific, arguing that developing rational thinking skills beyond traditional scientific methods is valuable and necessary.
Scott Alexander analyzes a study revealing poor statistical literacy among doctors, critiquing both the study and its implications for medical decision-making.
Scott examines neurological theories explaining delusions like Capgras syndrome through Bayesian reasoning, arguing that damage to the right prefrontal cortex causes patients to ignore priors and base their beliefs solely on explanatory adequacy.
Scott asks readers for examples of popular, important, factual questions with high uncertainty and no clear 'responsible' position, to use when teaching probabilistic thinking, noting that his previous examples like global warming have become too polarized.
Scott argues against Eliezer's position that reversed stupidity is never intelligence, showing that observing many people believe something for bad reasons can help identify 'popular claims' that people assert regardless of truth, which lets you properly discount future assertions of those claims.
Scott distinguishes between an argument's internal confidence level and our external confidence in that argument, showing that extremely high probability claims should be moderated by the baseline probability that the argument itself is flawed.
Scott analyzes when assertions should be trusted, showing that their evidentiary value depends on whether you already know the belief's distribution, the asserter's credentials, and how you encountered them, while claims of having 'evidence' mostly serve as signals of rationality rather than factual proof.